We propose that collagen features, such as alignment, fiber straightness and width, and other features of extracellular matrix composition can be used as an early biomarker of breast cancer. It is the goal of this proposal to determine the range of collagen structural features that characterize normal, benign and early disease, to determine how these features relate to mammographic density, and to identify the features that best predict risk, recurrence, and progression. This proposal leverages a diverse collaborative team that includes experts in imaging and understanding the tumor microenvironment, breast surgery, experts in population health and biostatistics, and an expert in proteomic analysis of the ECM. This team will analyze a set of patient cohorts to develop imaging and analysis of collagen structure and ECM composition as a potential early biomarker for breast cancer. Aims: 1) Characterize collagen features that define heterogeneity of the normal state. 2) Characterize collagen features in pre- and early breast cancer lesions. 3) Characterize the proteomics of biopsies representing benign, at risk, and invasive breast cancer. Significance: This project meets the goals of the RFA to develop and validate combined imaging and biomarker approaches to improve early cancer detection and the diagnosis of early-stage cancers. Our findings have the potential to reduce overdiagnosis and false positives and discern lethal from non-lethal disease.